Predictive Analytic Techniques for enhancing marketing performance and Personalized Customer Experience

Abstract

Marketing has always been seen as more of an art than a science. Marketing analytics has mainly demonstrated marketing's commercial impact by evaluating awareness, interest, and campaign results. However, as new markets are opening due to e-commerce and digitization, having the correct approaches, models, and tools for analyzing the quintillion bytes of data produced regularly is critical. Predictive data analytics is a method that can help with this new challenge as it is a development of previous data analytics models that predicts what will happen in the future by analyzing past data, detecting trends, and using that information to make forecasts about the industry's general trajectory. ML and AI are used to fuel predictive analytics' models and discoveries. These models dictate what and when a user sees across the board, from customer service to social media to FinTech; the technology is highly accurate, making it a valuable tool for firms in various industries that deal with terabytes of data. This research paper aims to discuss the predictive analytics models for enhancing marketing performance and personalized customer experience. It proposes that consumers are ready for a new journey in which predictive analytics is a tool for endless options, and information that is curated in a personalized way and explores how predictive analytics models can accurately determine consumer preferences and add a cognitive component to the otherwise traditionally human-powered and automated tasks.